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1. Constraints on simplified dark matter models involving an s-channel mediator with the ATLAS detector in pp collisions at $$\sqrt{s} = 13$$ TeV

   https://doi.org/10.1140/epjc/s10052-024-13215-5  

   Aad, G; Aakvaag, E; Abbott, B; Abdelhameed, S; Abeling, K; Abicht, N J; Abidi, S H; Aboelela, M; Aboulhorma, A; Abramowicz, H; et al (October 2024, The European Physical Journal C)

   Abstract This paper reports a summary of searches for a fermionic dark matter candidate in the context of theoretical models characterised by a mediator particle exchange in thes-channel. The data sample considered consists ofppcollisions delivered by the Large Hadron Collider during its Run 2 at a centre-of-mass energy of$$\sqrt{s} = 13\,\textrm{TeV}$$ $\sqrt{s}=13\text{TeV}$and recorded by the ATLAS detector, corresponding to up to 140 fb$$^{-1}$$ $_{}^{-1}$. The interpretations of the results are based on simplified models where the new mediator particles can be spin-0, with scalar or pseudo-scalar couplings to fermions, or spin-1, with vector or axial-vector couplings to fermions. Exclusion limits are obtained from various searches characterised by final states with resonant production of Standard Model particles, or production of Standard Model particles in association with large missing transverse momentum. 

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2. Global Trends of Axial Relief and Faulting at Plate Spreading Centers Imply Discrete Magmatic Events

   https://doi.org/10.1029/2020JB019465  

   Liu, Zhonglan; Buck, W. Roger (July 2020, Journal of Geophysical Research: Solid Earth)

   Abstract Observed variations in across‐axis topographic relief and faulting style at spreading centers have been challenging to explain. Axial highs are seen at fast‐spreading centers, while valleys occur for slow‐spreading centers. Fault offsets range from tens of meters at fast‐spreading ridges to tens of kilometers at some slow‐spreading ridges. Models that fit the axial relief fail to produce observed fault patterns, while models that fit the fault patterns fail to produce observed variations in axial relief. A recent mechanical analysis (Liu & Buck, 2018,https://doi.org/10.1016/j.epsl.2018.03.045) suggests that including the effect of many discrete diking events can result in a gradual change in axial relief with crustal thicknesses. To compare this mechanical model directly with observations requires us to couple it with a two‐dimensional thermal model. This allows us to estimate the axial lithospheric thickness consistently as a function of the spreading rate and crustal thickness. For thinner axial lithosphere the model predicts an axial high with relief supported by low‐density material beneath the axial lithosphere. For axial lithospheric thickness between approximately one half and approximately three fourths of the crustal thickness, the axial depth decreases with magma supply increase. For thicker axial lithosphere the axial valley relief is controlled by axial brittle lithospheric thickness and near‐axis lithospheric geometry. We compared model predictions to data by compiling observations on axial relief and faulting mode for all spreading centers where seismic crustal thickness has been measured. Good fit to the data is obtained for model parameters giving dike widths in the axial lithosphere close to a meter. 

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3. A machine-learning tool to predict substrate-adaptive conditions for Pd-catalyzed C–N couplings

   https://doi.org/10.1126/science.adg2114  

   Rinehart, N. I.; Saunthwal, Rakesh K.; Wellauer, Joël; Zahrt, Andrew F.; Schlemper, Lukas; Shved, Alexander S.; Bigler, Raphael; Fantasia, Serena; Denmark, Scott E. (September 2023, Science)

   Machine-learning methods have great potential to accelerate the identification of reaction conditions for chemical transformations. A tool that gives substrate-adaptive conditions for palladium (Pd)–catalyzed carbon-nitrogen (C–N) couplings is presented. The design and construction of this tool required the generation of an experimental dataset that explores a diverse network of reactant pairings across a set of reaction conditions. A large scope of C–N couplings was actively learned by neural network models by using a systematic process to design experiments. The models showed good performance in experimental validation: Ten products were isolated in more than 85% yield from a range of couplings with out-of-sample reactants designed to challenge the models. Importantly, the developed workflow continually improves the prediction capability of the tool as the corpus of data grows. 

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4. High-Level Data Fusion Enables the Chemoinformatically Guided Discovery of Chiral Disulfonimide Catalysts for Atropselective Iodination of 2-Amino-6-arylpyridines

   https://doi.org/10.1021/jacs.2c08820  

   Rose, Brennan T.; Timmerman, Jacob C.; Bawel, Seth A.; Chin, Steven; Zhang, Haiming; Denmark, Scott E. (December 2022, Journal of the American Chemical Society)

   Machine-learning methods have great potential to accelerate the identification of reaction conditions for chemical transformations. A tool that gives substrate-adaptive conditions for palladium (Pd)–catalyzed carbon-nitrogen (C–N) couplings is presented. The design and construction of this tool required the generation of an experimental dataset that explores a diverse network of reactant pairings across a set of reaction conditions. A large scope of C–N couplings was actively learned by neural network models by using a systematic process to design experiments. The models showed good performance in experimental validation: Ten products were isolated in more than 85% yield from a range of couplings with out-of-sample reactants designed to challenge the models. Importantly, the developed workflow continually improves the prediction capability of the tool as the corpus of data grows. 

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5. Global constraints on non-standard neutrino interactions with quarks and electrons

   https://doi.org/10.1007/JHEP08(2023)032  

   Coloma, Pilar; Gonzalez-Garcia, M C; Maltoni, Michele; Pinheiro, João Paulo; Urrea, Salvador (August 2023, Journal of High Energy Physics)

   A<sc>bstract</sc> We derive new constraints on effective four-fermion neutrino non-standard interactions with both quarks and electrons. This is done through the global analysis of neutrino oscillation data and measurements of coherent elastic neutrino-nucleus scattering (CEνNS) obtained with different nuclei. In doing so, we include not only the effects of new physics on neutrino propagation but also on the detection cross section in neutrino experiments which are sensitive to the new physics. We consider both vector and axial-vector neutral-current neutrino interactions and, for each case, we include simultaneously all allowed effective operators in flavour space. To this end, we use the most general parametrization for their Wilson coefficients under the assumption that their neutrino flavour structure is independent of the charged fermion participating in the interaction. The status of the LMA-D solution is assessed for the first time in the case of new interactions taking place simultaneously with up quarks, down quarks, and electrons. One of the main results of our work are the presently allowed regions for the effective combinations of non-standard neutrino couplings, relevant for long-baseline and atmospheric neutrino oscillation experiments. 

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